Andrzej Wąsowski 🟥I have written up a more detailed post about linear regression with #probula using grid approximation. The post focuses on:
- Explaining the example of linear regression in
probula(which is an internal DSL embedded in Scala 3) - Showing how grid approximation is implemented in
probula - Discussing how this implementation is tested and how is it used in testing of other #BayesianInference methods
Enjoy!
https://wasowski.dukla.ch/posts/2606-grid-approximation-with-probula/
#ProbabilisticProgramming #Bayesian #Inference #DataAnalysis #Scala #Scala3 #keep
Simple Univariate Regression with Grid Approximation in Probula
Let me share an update on probula, my small purely-functional Bayesian inference library written in Scala 3. The primary goal for this write-up is to force myself (and you) to think about testing of probabilistic models, of inference algorithms, and the languages or APIs in which they are formulated. Arguably, this is a very modest start. But more is on the way! I would like to start with the first inference scheme you encounter, when reading McElreath’s Statistical Rethinking. Grid approximation (as this is the scheme we speak about) is by far the least efficient of the methods discussed in the book, but it remains useful as a testing baseline. Its simplicity and determinism let it serve as ground truth and oracle for other, more complex inference methods.
Andrzej Wąsowski ☑️ 🟥
Andreas Kröpelin
Pierre-Simon Laplace
Adam Fleischhacker
Martin Trapp
José A. Alonso
Lawrence Murray
Martin Modrák